Modelling, Veriﬁcation and Validation of the IEEE

802.15.4 for Wireless Networks

P. S. Sausen

, P. F. Ribeiro Neto

A. Perkusich, A. M. N. Lima, M. L. B. Perkusich

and F. Salvadori

Technology Department

UNIJU

I, Iju

ı - RS - Brazil

Informatic Department

State University of Rio Grande do Norte, Mossor

o - RN - Brazil

Electrical Engineering Department

Federal University of Campina Grande, Campina Grande - PB, Brazil

Abstract. The purpose of this paper is to present a model of an mechanism Car-

rier Sense Multiple Access - Collision Avoidance unslotted capable of accessing

the environment. This mechanism is utilized in the latest IEEE 802.15.4 stan-

dard, which deﬁnes the wireless Medium Access Control and the Physical layer-

speciﬁcation for Low-Rate Wireless Personal Area Networks. For the model con-

struction, Hierarchical Coloured Petri Nets will be used. Hierarchical Coloured

Petri Nets are extensions of Coloured Petri Nets. Design/CPN tools will be used

for simulations, and the model will be veriﬁed and validated by means of occur-

rence graphs generation.

1 Introduction

The Low-Rate Wireless Personal Area Networks (LR-WPAN) is a new default in wire-

less networks developed by the Institute of Electrical and Electronic Engineers (IEEE)

and the National Institute of STandards (NIST) to transmit information to short dis-

tances at a low rate. The LR-WPAN operates within a Personal Operating Space (POS)

of 10 m or less. The LR-WPAN makes use of data rate of 20 Kb/s and an upper bound

of 250 Kb/s [1].

The LR-WPAN speciﬁed by IEEE 802.15.4 standard, is used for low cost equipment

with serious restrictions as to power consumption, the operation of which does not

require high rate transfers [2,3].

The IEEE has, recently, deﬁned a group of established smart sensor interfaces with

the IEEE 1451.5 speciﬁcations [4]. Such speciﬁcations adopt both the ZigBee associ-

ation and the IEEE 802.15.4 technology in sensor networks applications for wireless

communication. The 802.15.4 technology deﬁnes the physical layer and the link layer,

whereas the grouping ZigBee deﬁnes the network and application layers [5].

The fast progress in the ﬁeld of microprocessors, new monitoring sensors, Micro-

ElectroMechanical System and wireless communication have fostered the development

Sausen P., Neto P., Perkusich A., Lima A., Perkusich M. and Salvadori F. (2005).

Modelling, Veriﬁcation and Validation of the IEEE 802.15.4 for Wireless Networks.

In Proceedings of the 3rd International Workshop on Modelling, Simulation, Veriﬁcation and Validation of Enterprise Information Systems, pages 49-57

DOI: 10.5220/0002574200490057

 SciTePress

and application of LR-WPAN in areas related to physical, chemical and biological

processes, among others.

Due to these limitations, the search for new protocols and techniques has greatly

increased, and has become an enormous challenge in this area. Such developments,

however, require a test network that, in most cases, is not feasible from an economic

viewpoint owing to the fact that these networks are made up of hundreds, sometimes,

thousands of very expensive sensor units.

Based on what has just been said, the construction of a computational model in

order to support both the reduction in power consumption and the optimization process

has become of crucial importance in terms of costs and complexity.

It will be presented in this paper a model analysis of the IEEE 802.15.4, mainly the

link layer, by means of an access protocol to the Carrier Sense Multiple Access - Colli-

sion Avoidance (CSMA-CA) unslotted environment. Nevertheless, few are the methods

for simulating, verifying and validating such systems. Among these methods, one can

ﬁnd the hierarchical coloured Petri nets. Hierarchical Coloured Petri Nets (HCPN) are

very much useful for modelling dynamic and concurrency systems, such as a wireless

sensor network.

The remaining sections of this paper have been organized as follows: Section 2 gives

full details of the mechanism CSMA-CA unslotted ; Section 3 presents a brief descrip-

tion of HCPN; Section 4 describes our Mechanism CSMA-CA unslotted HCPN model;

Section 5 presents an analysis of the model; and Section 6 exhibits the conclusions and

points towards further developments.

2 Deﬁning the Mechanism CSMA-CA

The CSMA-CA mechanism is utilized in various network technologies, especially in

wireless technologies (e.g. in IEEE 802.ll and 802.15.4). This is a contention based-

mechanism that attempts to avoid a collision situation in the network by checking the

channel before transmission. Should the mechanism ﬁnd the channel busy, a random

time, termed backoff, is then devised so as to try again until it accesses the channel;

either by reaching or even exceeding the backoff. In such cases, transmission fails, and

the frame is retransmitted [5].

The CSMA-CA algorithm cannot be used for beacon frame transmissions, acknowl-

edgement frames or data transmitted over a Contention-Free Period (CFP). The LR-

WPAN employs two different kinds of mechanism in order to access the channel: the

CSMA-CA slotted or the CSMA-CA unslotted; the CSMA-CA slotted being out of the

scope of this paper. Further information regarding this mechanism can be found in [1].

For the mechanism LR-WPAN unslotted, any devices in need of transmitting data or

Medium Access Control (MAC) commands must wait for some random time. Transmis-

sion will only be possible when the channel becomes free after the backoff; otherwise,

the device will create another backoff and attempts to access the channel once again.

Such procedure will be repeated until the channel is accessed, or until waiting upper

limits are achieved. Further details about these limits will be given later in this paper.

Figure 1, redrawn from [1], shows the CSMA-CA unslotted algorithm, where vari-

ables NB (Number Backoff (periods)) and BE (Backoff Exponent) are initialized in

CSMA-CA

unslotted

Success

Failure

Channel

Idle?

NB >

macMaxCSMA

Backoff?

NB = 0

BE = macMinBE

Delay for Random

(2 

BE 

- 1)

Unit Backoff Periods

Perform CCA

NB = NB +1

BE = min(BE+1, aMaxBE)

Yes

No

(1)

(2)

(3)

(4)

Yes

No

Fig.1. The CSMA-CA unslotted algorithm

step 1, with the values zero and macMinBe, respectively. The macMinBe exhibits

value 3 as default. After completion of step 2, the backoff calculation is carried out.

This can vary from zero to (2

− 1) backoff units, a value that is deﬁned by variable

aUnitBackof f period with a default value that equals 20.

Step 3 provides for the Clear Assessment (CCA). Here one veriﬁes whether the

channel is capable of transmitting data successfully. If otherwise, step 4 will be taken,

where the NB and BE values are applied in 1. However, BE values should not be

greater than aMaxBE, whose default value is 5. Still in step 4, one veriﬁes if the NB

value is greater or equal to the macMaxCSM ABackoff , which has the default value

for 4. If so, transmission is aborted, or returns to step 2.

CCA represents the waiting procedure deﬁned by the backoff, which comes as a

result of the channel propagation delay, transmission delay, and other parameters, de-

pending on the physical environment. Further details can be found in [1].

3 Coloured Petri Nets Introduction

The basic foundation used for the modelling is that of the Hierarchical Coloured Petri

Nets, which is a Coloured Petri Nets extension [6]. HCPN is a suitable modelling lan-

guage used for task veriﬁcation, for they can express concurrency, parallelism, non-

determinism and different levels of abstraction needed by the channel access mech-

anism, e.g. CSMA-CA unslotted [7]. The HCPN considers modelling at hierarchical

levels. This has been made possible by the inclusion of two mechanisms: the substitu-

tion transition, and the fusion places. A substitution transition is a transition that can be

replaced by a CPN page [6].

Modelling requires a set of computational tools for editing, simulation and analysis.

The Design/CPN [8] consists of a package of four computational tools for developing

hierarchical coloured Petri nets.

4 HCPN Model of Mechanism CSMA-CA Unslotted

The HCPN model of mechanism is described in 3 pages that models the mechanism.

There is still another page that deﬁnes the types, data structures and the functions

needed to secure its perfect functioning. The model global declarations encompass the

types and variables of the mechanisms CSMA-CA unslotted.To follow a summarized

description of these paginas will be made.

4.1 Declarations

The model global declarations encompass the types and variables of the mechanisms

CSMA-CA unslotted. Figure 2 shows all the types and variables of the model, described

as follows: BE, Backoff Exponent is the exponent used to calculate the CSMA-CA

Backoff period;VB, value Backoff is used to store the calculated value from BE and

from the random period;NB, number Backoff is used to control most backoff numbers

resulting from each transmitting cycle.

The CSMA-CA holds 4 constants that are initialized with values deﬁned by the

IEEE 802.15.4 standard [1]. These are: macminbe which is the minimum value of BE

in the CSMA-CA algorithm; macMaxCSMABackoff which is the maximum number

of backoff; aU nitBackof fP eriod , which is the number of symbols forming the ba-

sic time period used by the CSMA-CA algorithm and amaxbe is the maximum value

attributed to the BE variable.

For the backoff calculus, a random number generator is speciﬁed by means of the

following variables: be3, be4 and be5, which are responsible for creating radom number.

4.2 Mechanism CMSA-CA Unslotted

Figure 3 shows the modelled mechanism CSMA-CA unslotted. The maximum veriﬁca-

tion limit (macMaxCSM ABackof f) is carried out by this model by means of transi-

tions N BV alid and NBInvalid, where these have the guards [nb <> 4] and [nb = 4],

respectively. If the limit is reached, as one can see in the algorithm shown in Figure 1,

a transmission failure is then detected, in which case, the sensor is re-initiated. This is

accomplished by the arc inscription of the ReSend (1‘(sensor, 3, 0, 0))transition, after

which the veriﬁcation is transmitted again; or else, the backoff calculus proceedings are

called forth by means of the CallBO place, which binds with the StartBO place, as

modelled in the BackOff Calc subpage, shown in Figure 4.

(* Global Declaration *)

color Sensor = with sensor1 | sensor2;

color Status = with livre | ocupado;

color Contador = int;

color BE = int;

color VB = int timed;

color NB = int;

color Tabela = product Sensor * BE * VB * NB;

color Relogio = product Status * Contador * Sensor * BE * NB timed;

var sensor:Sensor;;

var status:Status;

var cont:Contador;

var be:BE;

var vb:VB;

var nb:NB;

(* MAC SubLayer Constant *)

val macminbe = 3 : int;

val amaxbe = 5 : int;

val aunitbackoffperiod = 20 : int;

val macminbe = 3 : int;

val amaxbe = 5 : int;

val macMaxCSMABackoff = 4 : int;

(*Constant of Calculate Backoff *)

color Int_0_7 = int with 0..7;

color Int_0_15 = int with 0..15;

color Int_0_31 = int with 0..31;

var be3:Int_0_7;

var be4:Int_0_15;

var be5:Int_0_31;

( * Function for Calculate OG *)

val gettimeofday : unit -> (Int32.int * int) =

Unsafe.CInterface.c_function "SMLNJ-Time" "timeofday"

fun tod() =

let

(* max int in SML on 32 bit machines (see Int.maxInt) *);

val maxint31 = Int32.fromInt 1073741823

val (secs, _) = gettimeofday()

(* convert back into "small integers" to preserve type *)

val secs31bit = Int.fromLarge(Int32.-(secs,maxint31))

secs31bit

end;

Fig.2. Colors Sets and Variables

IfNB

Tabela

NBInvalid

[nb=4]

Error

Tabela

Sensors

Tabela

Transmit

ReSend

NBValid

[nb<>4]

CallBO

Tabela

TransFail

Tabela

(sensor,be,vb,nb)

1‘(sensor,3,0,0)

(sensor,be,vb,nb)

Fig.3. CPN Model for CSMA-CA.

When simulation is completed, one can see, on the ﬁnal marking at T ransF ail,

the number of sensors that exceeded the backoff maximum limit, and as a result, had

to initiate a re-transmission. It is on this page that sensors are inserted into our model,

mainly, on account of the initial marking of the Sensors place. Once sensors are de-

ﬁned, transmission is carried out with success bringing simulation to an end in a case

where no feedback was needed.

The fusion place of the CSMA−CA page was obtained through an AccessChannel

subpage whose description can be found in Section 4.4. This will supply this page with

the sensors’ trafﬁc. The latter will ﬁnd the busy channel after a backoff initial period.

4.3 BackOffCalc

The BackOf f page, shown in Figure 4, models the backoff calculus procedure. This

page is summoned by CSM A − CA page from which it obtains the sensors’ trafﬁc,

going through steps 1, 2 and 3 of the algorithm shown in Figure 1. The CaseBE and

CompBE transitions arcs work out the BE calculus and determine the random waiting

value. Both are shown in step 2 of Figure 1. After calculating the random time period,

the model uses up its time through the expression @+vb, which is the StarT ime transi-

tion guard. The backoff calculus procedure is completed in the SendAccChann place,

which is the fusion place with the AccessChannel page. This page will be described

in Section 4.4.

DefBe

Tabela

CompBE

AddTime

Tabela

StartTime

@+vb

BOTime

Relogio

EndBackO

ConvSenso

Tabela

EndBOSens

StartBO

Tabela

CaseBE

SendAccChann

Tabela

(sensor,be,vb,nb)

if ((be+1) >= 5)

then 1‘(sensor,5,vb*aunitbackoffperiod,nb)

else 1‘(sensor,be+1,vb*aunitbackoffperiod,nb)

(sensor,be,vb,nb)

(livre,vb,sensor,be,nb)

(status,cont,sensor,be,nb)

(sensor,be,0,nb)

(sensor,be,vb,nb)

case be of

3=>1‘(sensor,be,be3,nb+1)|

4=> 1‘(sensor,be,be4,nb+1)|

5=> 1‘(sensor,be,be5,nb+1)

(sensor,be,vb,nb)

Fig.4. CPN Model for BackOffCalc.

ChFree

[status=livre]

ChAcess

Tabela

AccCh

Tabela

ChSend

[status=ocupado]

ChBusy

[status=ocupado]

Manage-

ment

Status

1‘livre

SendOK

Tabela

ChBusyEnd

Tabela

ReturnBus

Status

StartM

(sensor,be,vb,nb)

status

1‘ocupado

(sensor,be,vb,nb)

status

1‘ocupado

(sensor,be,vb,nb)

1‘livre

Fig.5. CPN Model for AccessChannel.

4.4 The AccessChannel

The AccessChannel page, described in Figure 5, is executed whenever a sensor at-

tempts to access the channel after a backoff period. The AccCh place provides the

sensors’ trafﬁc, which is the fusion place with the SendAccChannel, as illustrated in

Figure 4. Here, the model checks if the channel is available by means of a CHF ree

transition with the guard status = f ree. Once the channel’s availability is attested, the

simulation procedure starts with the free set given by the M anagement place initial

marking, as shown in Figure 5. With the occurrence of CHF ree transition, a token with

a status that says busy in the Management place, will be positioned. The ChBusy

transition is then enabled, owing to its guard (status = busy). The channel remains

busy until a ChSend transition ﬁres, indicating end of transmission.

On the other hand, whenever the ChBusy transition is enabled, it means that there

exist transmitting sensor and that the channel (ChF ree) is busy. In case one gets a

ChBusy, a token is then positioned in the ChBusyEnd place. As a result, a new

backoff calculus is needed, as this is the fusion place with StartBO, as illustrated in

Figure 4.

This page models a situation that is common to occur with the mechanism CSMA-

CA unslotted, which is a sensor to transmit and detect the busy channel. The NB is

then increased to 1, being necessary to re-calculate the backoff period, as described in

step 4 in Figure 1, and to model it on the BackOff Calc page (Fig. 4).

5 Model Analysis

For the model analysis, different scenarios have been considered in order to verify the

properties and to validate them in relation to the mechanism CSMA-CA unslotted. The

scenarios are established by the quantity of sensors deﬁned in the model. However,

for these scenarios, two, ten and twenty sensors are taken into account. The Sensors

place initial marking corresponds to the number of sensors, as shown in Figure 3. The

model gets to its ﬁnal state when all sensors, speciﬁed in the initial marking, reach the

SendOk place, as shown in Figure 5. It must be noticed that different markings may be

admitted to the ﬁnal state, because a token can be represented by the color, and these

may assume different values in accordance with backoff value.

Statistics

----------------------------------------------------------

Occurrence Graph

Nodes:18448 Arcs:31036 Secs:18301 Status:Full

Boundedness Properties

----------------------------------------------------------

Best Integers Bounds Upper Lower

CSMA’AccCh 1 2 0

CSMA’AddTime 1 2 0

CSMA’ChAcess 1 1 0

CSMA’DefBe 1 2 0

CSMA’Error 1 1 0

CSMA’IfNB 1 2 0

CSMA’Management 1 1 0

CSMA’ReturnBusy 1 1 0

CSMA’SendOK 1 2 0

CSMA’Sensors 1 2 0

CSMA’Time 1 2 0

Liveness Properties

----------------------------------------------------------

Dead Markings:1400 [9986,9945,..]Dead Trans.Instances:None

As one may have noticed before, by means of occurrence graphs, it is possible to

verify the properties inherent to the model. Occurrence graphs are directed graphs that

can present a node for each reachable marking and an arc for each binding element.

An arc binds the marking node, here the associated binding element comes from the

resulting marking node of occurrence.

The Design/CPN graph tools will permit report emission with the general properties

of the model. This report contains information on the graph and on the properties that

are useful to understand the model’s behavior in HCPN.

Considering the scenario for two sensors, the report sent with the general properties

contains the node number, arc number, and the time needed for its full generation. The

scenario for two sensors, considered in the occurrence graph, follows as a result of

this, regarding all possible sequences including the concurrency between sensors so

as to access the channel. Should one consider only one sensor, some dead transition

instances will be identiﬁed, in which case there will be no concurrency.

As for the boundedness properties, it is important to show the following places:

Sensors, SendOK and ChAccess. For the Sensors place and SendOK the upper

and lower bounds are two and zero, respectively. These places represent the number of

sensors in the scenario. The upper bound to the place ChAcess is one, since this place

illustrates the channel, and only a sensor can access the channel.

With the liveness properties, described in the report, one can verify the absence of

dead transitions instances. For such, the number of dead markings is identiﬁed as a state

explosion, due to the acceptable backoff number. This is shown in Section 4.

With the various simulations covering the scenarios two, ten and twenty sensors,

one may deduce that the model presents only correct end states and deadlock free. The

correct end states are illustrated by the SendOK place, shown in Figure 5, where all

sensors for the ﬁnal simulation are to be found.

The properties considered above are signiﬁcant for validating the model, for the

channel represented by the ChAccess place can only have one sensor at a time. The

SendOK shows the sensors that were successfully transmitted.

6 Conclusions

The main contribution of the present research is the setting up of a formal model def-

inition, using Coloured Petri Nets for the IEEE 802.15.4 Link Layer. By means of this

model, it will be possible to develop techniques for the reduction of power consumption

and for the optimization process.

The model we propose to represent such standard proved to be coherent. The model

was checked by means of an occurrence graph tool through which each place maximum

and minimum markings were obtained. It was also possible to investigate transmission

failure occurrences by a ﬁnal marking of the T ransF ail place, i.e. when a sensor at-

tempts to access the medium four times over, only to ﬁnd it busy. The model validation

is obtained by the ﬁnal marking of the SendOK place. At the end of simulation, all

items speciﬁed by the initial marking must be presented this place, in spite of the fact

that some attributes may exhibit different values. By means of these values, it is possible

to verify the network loading state.

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